We present stability and control analysis of a rider- bicycle system under human steering and body movements. The dynamic model of rider-bicycle interactions is first constructed to integrate the rider's body movement with the moving bicycle platform. We then present human balance control strategies based on human riding experiments. The closed-loop system stability is analyzed and discussed. Quantitative influences of the bicycle physical parameters, the human control gains, and the time delays are also analyzed and discussed. Extensive experiments are conducted to validate the human control models and demonstrate human balance performance using the bikebot, an instrumented bicycle platform. The presented modeling and analysis results can be potentially used for further development of bicycle-assisted rehabilitation for postural balance patients.

We present trajectory tracking and balance control of an autonomous bikebot. The bikebot is a single-track autonomous mobile robot that is designed to study unstable physical human-robot interactions. The controller is built on the property of the external-internal convertible (EIC) structure for the bikebot dynamics. We present two types of the designs and analyses of the control systems and also demonstrate their performance through extensive experiments. The comparison results with the human riding experiments show that the rider's motor skills generate the similar strategies as the proposed EIC-based balance control.

We present the development of the gyroscopic-balanced control of an autonomous bikebot. The bikebot is an actively controlled bicycle-based robotic platform with a gyro-balancer developed to study human dynamic postural balance motor skills through unstable physical human-robot interactions. We also present a dynamic model and analysis for stationary bikebot. A nonlinear balancing controller is designed to stabilize the underactuated stationary bikebot on an orbital trajectory around the unstable equilibrium point that is coupled with another orbit of the actuated gyro-balancer. We then demonstrate the analysis and control design with experimental validations. Finally, we present a set of human riding experiments to show how the bikebot can be used to perturb and excite human sensorimotor feedback loop for dynamic postural balance motor skills.

Underwater autonomous gliders (UAG) such as Slocum electric gliders provide an effective platform and tool for marine and coastal scientists to conduct prolonged missions over weeks or months. However, localization of these gliders underneath ocean surface is challenging due to the lack of inexpensive, effective underwater positioning sensors. In this paper, we present a dynamic model-based localization scheme to improve the positioning estimation of UAG. The new localization approach is built on an experimentally validated dynamic model and fused with onboard depth and yaw angle sensor measurements. We compare and validate the proposed scheme with dead reckoning and the ground truth.